Abstract
In recent years, the impact of the resilience of workers has been widely recognized in dealing with unexpected system behavior and unknown situations to safely operate complex socio-technical systems such as aviation, railroad, medical, and nuclear plants. Resilience coping flexibly with novel events and avoiding failures or worst-case scenarios is concretely defined as four-resilience potential (RP), which are responding, monitoring, learning, and anticipating. In this research, we aim to realize a human-system interaction to support the improvement of RP of workers. As the first step, we conducted a cognitive experiment to characterize workers' RP when they must respond to a significant situation change. In the experiment, we classified participants into two groups: an HS group with high Non-Technical Skill (NTS) and an LS group with low NTS. The results revealed the following: (1) The correlation between NTS and task performance is low under normal conditions, (2) In an emergency when significant changes in circumstances occur, the HS group may have relatively higher RP than the LS group, and (3) The HS group always tends to perform tasks with an awareness of the target values and a detailed understanding of the situation. These characteristics of the HS group may contribute to demonstrating resilient performance.
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Acknowledgment
Professor Etsuko Harada and the Harada Laboratory at the University of Tsukuba provided the Breakfast Cooking Challenge application used in this experiment. We sincerely appreciate their kindness.
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Yoshida, H., Ikeda, T., Karikawa, D., Aoyama, H., Kanno, T., Toriizuka, T. (2023). Analysis of Resilient Behavior for Interaction Design. In: Mori, H., Asahi, Y. (eds) Human Interface and the Management of Information. HCII 2023. Lecture Notes in Computer Science, vol 14015. Springer, Cham. https://doi.org/10.1007/978-3-031-35132-7_13
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DOI: https://doi.org/10.1007/978-3-031-35132-7_13
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